Leonie Roos and Nevena Cvetesic
11. 01. 2017.
dataframes & matrices returned by CAGEr functions:
Per individual sample ( raw or normalized tag counts)
Across samples (one output for multiple samples)
These can be easily manipulated by the user in R.
We'll go through this in more detail in the tutorial
Other than consensus clusters most data is extracted per sample as they are sample specific
Likely you want to perform the same analyses, checks, plots, etc for all the samples.
Solution?
Automate what you're doing! Functions are great to avoid mistakes
We'll create a few of these in the tutorial
Where does most of the signal fall?
Nepal, C., et al. (2013). Dynamic regulation of coding and non-coding transcription initiation landscape at single nucleotide resolution during vertebrate embryogenesis. Genome Research, 23(11):1938-1950.
we count the overlap our TCs per sample for each feature and count the occurances per sample:
Promoter interquantile widths
ggplot2 to create other types of graphs than CAGEr offers
Distinguishing features of sharp and broad promoters